Real-time FFT algorithm applied to on-line spectral analysis

Abstract

On-line running spectral analysis is of considerable interest in many electrophysiological signals, such as the EEG (electroencephalograph). This paper presents a new method of implementing the fast Fourier transform (FFT) algorithm. Our "real-time FFT algorithm" efficiently utilizes computer time to perform the FFT computation while data acquisition proceeds so that local butterfly modules are built using the data points that are already available. The real-time FFT algorithm is developed using the decimation-in-time split-radix FFT (DIT sr-FFT) butterfly structure. In order to demonstate the synchronization ability of the proposed algorithm, the authors develop a method of evaluating the number of arithmetic operations that it requires. Both the derivation and the experimental result show that the real-time FFT algorithm is superior to the conventional whole-block FFT algorithm in synchronizing with the data acquisition process. Given that the FFT size N = 2(r), real-time implementation of the FFT algorithm requires only 2/r the computational time required by the whole-block FFT algorithm.